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## ========================================
## ComplexHeatmap version 2.18.0
## Bioconductor page: http://bioconductor.org/packages/ComplexHeatmap/
## Github page: https://github.com/jokergoo/ComplexHeatmap
## Documentation: http://jokergoo.github.io/ComplexHeatmap-reference
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## If you use it in published research, please cite either one:
## - Gu, Z. Complex Heatmap Visualization. iMeta 2022.
## - Gu, Z. Complex heatmaps reveal patterns and correlations in multidimensional
## genomic data. Bioinformatics 2016.
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## The new InteractiveComplexHeatmap package can directly export static
## complex heatmaps into an interactive Shiny app with zero effort. Have a try!
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theme(text = element_text(size=10, colour='black'),
title = element_text(size=10, colour='black'),
line = element_line(linewidth=0.5),
axis.title = element_text(size=10, colour='black'),
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## generated.## Rows: 5889744 Columns: 15
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: "\t"
## chr (12): ENSG, chr, start, end, strand, gene_name, gene_type, ID_NGS, ID_SC...
## dbl (3): length, count, RCB_score
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## chr (12): chr, circ_id, strand, circ_type, ID_NGS, ID_SCAND, chemo_status, s...
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## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.filter data based on counts
fc = fc %>%
filter(sample_origin == 'patient') %>%
group_by(ENSG) %>%
filter(any(count >= 20)) %>%
ungroup()
fc